Package: serodynamics 0.1.0
Samuel Schildhauer
serodynamics: Modeling Longitudinal Antibody Responses to Infection
Implements Bayesian hierarchical models for estimating antibody kinetic parameters from longitudinal serological data. Fits two-phase within-host models capturing antibody rise, peak, and decay following pathogen infection, using 'JAGS' for posterior inference. Designed as the upstream companion to the 'serocalculator' package for end-to-end seroepidemiological analysis. Methods are described in Teunis and colleagues (2016) <doi:10.1016/j.epidem.2016.04.001> and Teunis and van Eijkeren (2020) <doi:10.1002/sim.8578>.
Authors:
serodynamics_0.1.0.tar.gz
serodynamics_0.1.0.tar.gz(r-4.7-any)serodynamics_0.1.0.tar.gz(r-4.6-any)
serodynamics_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
serodynamics/json (API)
NEWS
| # Install 'serodynamics' in R: |
| install.packages('serodynamics', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/ucd-serg/serodynamics/issues
Pkgdown/docs site:https://ucd-serg.github.io
- jags– Just Another Gibbs Sampler for Bayesian MCMC - binary JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS was written with three aims in mind: * To have an engine for the BUGS language that runs on Unix * To be extensible, allowing users to write their own functions, distributions and samplers. * To be a plaftorm for experimentation with ideas in Bayesian modelling This package contains the 'jags' binary as well as the associated shared library modules loaded by the binary.
- c++– GNU Standard C++ Library v3
- nepal_sees - SEES Typhoid data
- nepal_sees_jags_output - SEES Typhoid run_mod jags output
Last updated from:cd0b7fc01f. Checks:4 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 180 | ||
| source / vignettes | OK | 221 | ||
| linux-release-x86_64 | OK | 231 | ||
| wasm-release | OK | 173 |
Exports:as_case_dataautoplotexpect_snapshot_dataget_biomarker_levelsget_biomarker_names_varinitsfunctionload_dataplot_jags_densplot_jags_effectplot_jags_Rhatplot_jags_traceplot_predicted_curvepost_summpostprocess_jags_outputprep_dataprep_priorsrun_modserodynamics_examplesim_case_datasim_n_obs
Dependencies:andbitbit64clicliprcodacodetoolscpp11crayondigestdoParalleldplyrfarverforcatsforeachgenericsGGallyggmcmcggplot2ggstatsgluegtablehavenhmsisobanditeratorslabelinglabelledlatticelifecyclemagrittrMASSpatchworkpillarpkgconfigprettyunitsprogresspurrrR6RColorBrewerRcppreadrrlangrngtoolsrunjagsS7scalesserocalculatorstringistringrtibbletidyrtidyselecttzdbutf8vctrsviridisLitevroomwithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Convert data into 'case_data' | as_case_data |
| Plot case data | autoplot.case_data |
| JAGS chain initialization function | initsfunction |
| load and format data | load_data |
| SEES Typhoid data | nepal_sees |
| SEES Typhoid run_mod jags output | nepal_sees_jags_output |
| Density Plot Diagnostics | plot_jags_dens |
| Plot Effective Sample Size Diagnostics | plot_jags_effect |
| Rhat Plot Diagnostics | plot_jags_Rhat |
| Trace Plot Diagnostics | plot_jags_trace |
| Generate Predicted Antibody Response Curves (Median + 95% CI) | plot_predicted_curve |
| Summary Table of Jags Posterior Estimates | post_summ |
| Postprocess JAGS output | postprocess_jags_output |
| prepare data for JAGs | prep_data |
| Prepare priors | prep_priors |
| Run Jags Model | run_mod |
| Get path to an example file | serodynamics_example |
| Simulate longitudinal case follow-up data from a homogeneous population | sim_case_data |
